1. Census Processing Baku Training Module

2.  Discuss:  Processing Strategies  Processing operations  Quality Assurance for processing  Technology Issues for processing  Questions Overview

3.  Strategic directions need to be established early in the census cycle.  Single most important decision is deciding upon the processing system to be used and the technologies that will be adopted.  These decision needs to be made early enough to enable sufficient time for testing and implementation. Census Processing

4. Data Processing Cycle

5.  Receipt and Registration  as enumeration area materials arrive, they are checked for completeness and "marked in"  close coordination with Field processes  Preliminary Checking  forms are groomed for later processes, e.g. transcribed if not suitable for later processes  Coding and Data Capture  information is captured off the forms and converted into the classification

6. Data Processing Cycle  Balancing  computer records are checked against the forms to ensure a record has been created for each person and dwelling enumerated  Validation  checks the data to ensure it meets minimum agreed standards  Quality Assurance and Editing  Editing used to make responses consistent with the form/sequence rules/classifications  Imputation used to correct non-response

7. Controlling the workflow  monitoring and controlling work flows needs close attention  Each activity depends on the quality and quantity of the output from previous activities.  Critical that each activity is meeting production targets to ensure that the following activity has sufficient work.  Delays in one activity can lead to costly lost production in the following activities.  Changes in procedures to raise production will have to be carefully considered to ensure that the quality of the data is not adversely affected.

8. Management Information Systems  An essential tool for managers at a processing centre is a Management Information System  The general requirements of a MIS are as follows :  to allow access to information to all managers  to ensure all information is timely and as detailed as possible  to forecast and report on outcomes for future activity within the processing centre  ensure information acquired in one Census, can be utilized for planning in future Censuses

9.  What to collect :  production rates  flow control  staffing  quality assurance  automatic edits  What to report :  production  automatic edits  quality assurance  feedback to individuals Management Information Systems

10. Quality Assurance  Quality of Census data is defined as multi-dimensional, involving elements of :  data accuracy  budget  timeliness  relevance

11. Quality Assurance  Quality Management Framework  Processing of census data is complex - each process relies on the quality of the preceding process.  To assist in obtaining the highest possible data quality a framework incorporating the following components can be established at a processing centre:  quality management system;  quality assurance points for each process;  continuous quality improvement processes;  validation of data.

12. Continuous Quality Improvement  Continuous Quality Improvement (CQI) is a core component of the Total Quality Management philosophy.  CQI aims to continue to improve the quality of the output of a project throughout the life of that project.  A continuous quality improvement approach can be implemented in the following ways :  using teams of processing staff to identify and resolve quality problems;  using quantitative measures of quality, based on discrepancies in the output of the process; and  giving priority to identifying and addressing the root causes of these discrepancies

13. Measuring quality Identify root cause Identify most important quality problem Measure Quality Implement corrective action  Quality Assurance Circle (or Continuous Quality Improvement)

14. Validation  The purpose of validating census data is to identify system problems and ensure data quality for final output.  Final check to ensure that the data produced by the processing system meets the specifications of the editing program and output requirements.  Validating the data before it leaves the processing centre ensures that errors that are significant and considered important can be corrected in the final file  Validating as you process ensures the issues found can be fed into improving the process as you go.

15.  The successful introduction of technology into the processing phase will have a large impact on the overall success of the census.  The nature of census processing (ie the capture and manipulation of large amounts of data) is ideally suited to computerised technology.  Use of technology like imaging and Intelligent Character Recognition (ICR) offers great potential and associated benefits for census processing.  BUT be aware of the lead times and technology infrastructure required for successful implementation of ICR. Technology Issues

16.  Data- capture methods  key entry  optical mark recognition  digital imaging/intelligent character recognition  electronic lodgment of forms (eg; Internet)  Coding  clerical/computer assisted  automatic coding Technology Options

17. Technology Issues  Data Management - issues to consider  networks and infrastructure  data storage  data backups  data security

18. Questions?

19. Working Group Exercise  Working in groups, answer the following:  What issues can reduce the quality of the information processed?  What can be put in place to reduce the impact of these issues?